Fuzzy Ontology Reasoning for Power Transformer Fault Diagnosis

被引：12

作者：

Samirmi, Farhad Davoodi ^{[1
]}

Tang, Wenhu ^{[2
]}

Wu, Qinghua ^{[1
,2
]}

机构：

[1] Univ Liverpool, Dept Elect Engn & Elect, Liverpool L69 3GJ, Merseyside, England

[2] S China Univ Technol, Sch Elect Power Engn, Guangzhou 510640, Peoples R China

来源：

ADVANCES IN ELECTRICAL AND COMPUTER ENGINEERING | 2015年 / 15卷 / 04期

基金：

国家高技术研究发展计划(863计划); 中国国家自然科学基金;

关键词：

Fault diagnosis; ontology; fuzzy sets; multi-agent systems; power transformer; IN-OIL ANALYSIS; REPRESENTATION; SYSTEM;

D O I：

10.4316/AECE.2015.04015

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a novel fuzzy ontology reasoner for power transformer fault diagnosis under a multi-agent framework. The developed ontology provides a comprehensive knowledge base as part of a multi-agent system to enable imprecision reasoning. It is the first time that a fuzzy ontology model is developed for accurate power transformer fault diagnosis. It aims to develop an improved ontology model for transformer fault diagnosis by applying the fuzzy ontology. The proposed technique deals with the imprecision situation using the fuzzy ontology, in order to build an ontology-based knowledge representation for accurate power transformer fault diagnosis. The proposed system is tested with actual transformer online data to demonstrate the functionality of the developed fuzzy ontology, which can identify the faults that are unidentifiable using a basic ontology model, and this can significantly improve the overall accuracy for transformer fault diagnosis under a multi-agent framework.

引用

页码：107 / 114

页数：8

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